Prioritizing new bicycle facilities to improve low-stress network connectivity |
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| Institution: | 1. Department of Civil Engineering, University of Idaho, Moscow, ID 83844, USA;2. Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA;3. Rails to Trails Conservancy, Washington, DC 20037, USA;1. Office of Archeological Research, University of Alabama, Tuscaloosa, AL 35487, United States;2. Department of Geography, University of Alabama, Tuscaloosa, AL 35487, United States;1. Safe Transportation Research and Education Center, University of California, Berkeley, 2614 Dwight Way, Berkeley, CA 94720, United States;2. Department of Civil and Environmental Engineering, University of California, Berkeley, 116 McLaughlin Hall, Berkeley, CA 94720, United States;3. University of Derby Online Learning, Enterprise Centre, Bridge Street, Derby DE1 3LD, United Kingdom;4. Department of Civil and Environmental Engineering, University of California, Berkeley, 111 McLaughlin Hall, Berkeley, CA 94720, United States |
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| Abstract: | This paper introduces a new method to prioritize bicycle improvement projects based on accessibility to important destinations, such as grocery stores, banks, and restaurants. Central to the method is a new way to classify “bicycling stress” using marginal rates of substitution which are commonly developed through empirical behavioral research on bicyclist route choice. MRS values are input parameters representing bicycling stress associated with the number of lanes and speed limit of a street. The method was programmed as a geographic information system tool and requires commonly available data. The tool is demonstrated on three improvement scenarios that were recently proposed for Seattle, Washington. The full build-out scenario consists of 771 projects that include various new bike lanes, protected bike lanes, and multi-use trails. The tool produces priority rankings based on a project’s ability to improve low-stress connectivity between homes and important destinations. The analysis identifies specific areas and neighborhoods that can be expected to exhibit better bikeability. Transportation planners can use the tool to help communicate anticipated project impacts to decision-makers and the public. |
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| Keywords: | Bicycle Accessibility planning Centrality Constrained shortest path Marginal rate of substitution |
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